Constraint-optimization system and method for document component layout generation

ABSTRACT

What is disclosed is a system and method for specifying a custom document as a multi-criteria constraint optimization problem, and a method to automatically create the specified document using existing constraint optimization solving algorithms. The present method specifies the document, its content components, its layout requirements, and its desired aesthetic criteria are expressed as elements of a constraint optimization problem which when solved, results in an automated document layout for the set of content components that satisfies not only certain primitive content and layout constraints, but which also advantageously fulfills desired design properties and which provides a way to ensure that the generated document is well designed. The method for automatic document layout comprises the steps of determining a set of variables that can be adjusted to achieve a satisfactory layout; expressing said satisfactory layout as a set of constraints on said determined set of variables wherein at least one of said set of constraints is expressed as being optimizable; and solving said constraints to find a layout which solves for the variables over the constraints. The system for automatic document layout on multi-function office equipment comprises means for document layout constraint acquisition; means for document layout variable specification which specifies a set of variables that can be adjusted to achieve a satisfactory layout; means for relationship-constraint to optimization-constraint conversion which expresses said satisfactory layout as a set of constraints on said set of variables wherein at least one of said set of constraints is expressed as being optimizable; and means for constraint optimization for solving said constraints to find a layout which solves for the variables over said constraints.

FIELD OF THE INVENTION

The present invention is directed to systems and methods to finddocument components and assemble them into a custom document such as avariable data document and, in particular, those systems and methodswhich use constraint-optimization approaches wherein the document, itscontent, components, and its requirements are expressed as a constraintoptimization problem.

BACKGROUND OF THE INVENTION

Custom documents are documents that are personalized or tailored in someway to the particular user of the document. Two growing applications ofcustom documents are in the domain of variable data printing, as well asin web personalization.

Traditional approaches to custom document creation are non-automated andtherefore user-intensive, and result in documents that are typicallyquite similar: the layout is the same for all instances, regardless ofthe available content pieces. Furthermore, the document creator isresponsible for ensuring that the final document adheres to good designprinciples, and is therefore aesthetically pleasing. Thus the documentcreator himself typically creates the document template according to hispreferred design criteria, which requires knowledge about documentdesign and how to best achieve the desired qualities in a particularinstance of the document.

Traditional creation of custom documents such as variable data documentsrequires expertise in many areas such as graphic arts and databases andis a time consuming process. With the ever-increasing amount ofinformation in the digital world and the amount of untrained usersproducing documents, old publishing tools often prove cumbersome anddemanding whereas present dynamic digital environments demand tools thatcan reproduce both the contents and the layout automatically tailored topersonal needs and which can enable novices to easily create suchdocuments.

Known methods for automated creation of documents have focused more onparticular types of documents, and not on modeling the problem in ageneral way in order to address all types of documents. Existing workprovides methods for creating diagrams (see Dengler, E. Friedell, M.,Marks, J., Constraint-Driven Diagram Layout, Proceedings of the 1993IEEE Symposium on Visual Languages, pages 330-335, Bergen, Norway,1993), or multimedia presentations (see Rousseau, F., Garcia-Macias, A.,Valdeni de Lima, J., and Duda, A., User Adaptable MultimediaPresentations for the WWW, Electronic Proceedings from the 8^(th)International World Wide Web Conference, 1999), or flowcharts and yellowpages (see Graf, W. H., The Constraint-Based Layout Framework LayLab andApplications, Electronic Proceedings of the ACM Workshop on EffectiveAbstractions in Multimedia, 1995). Others have explored automating theprocess of web document layout (see Kroener, A., The Design Composer:Context-Based Automated Layout for the Internet, Proceedings of the AAAIFall Symposium Series: Using Layout for the Generation, Understanding,or Retrieval of Documents, 1999).

Known methods for a constraint-optimization approaches to documentlayout use a single optimization criterion: cost, and model their layouttask as finding an ordering of stories and advertisements that canminimize the production cost as described in U.S. Pat. No. 6,173,286.The present invention differs in that it offers a more general model forrepresenting a layout problem as a constraint optimization problem,enables the specification of multiple optimization criteria, andprovides a process by which to combine required and optimizationconstraints in order to achieve a well-designed document.

What is needed in the arts in order to ensure that an automaticallyassembled document also meets desired aesthetic design criteria, is away to model document creation as a multi-criteria optimization problem,allowing the specification of both required layout constraints as wellas desired aesthetic qualities of the output document, and a means toautomatically process this combination of hard and soft constraints toautomatically generate a well-designed document.

SUMMARY OF THE INVENTION

What is disclosed is a system and method for specifying a customdocument as a multi-criteria constraint optimization problem, and amethod to automatically create the specified document using existingconstraint optimization solving algorithms. The present method specifiesthe document, its content components, its layout requirements, and itsdesired aesthetic criteria as elements of a constraint optimizationproblem which when solved, results in an automated document layout forthe set of content components that satisfies not only certain primitivecontent and layout constraints, but also advantageously fulfills desireddesign properties and which provides a way to ensure that the generateddocument is well designed. The method for automatic document layoutcomprises the steps of determining a set of variables that can beadjusted to achieve a satisfactory layout; expressing said satisfactorylayout as a set of constraints on said determined set of variableswherein at least one of said set of constraints is expressed as beingoptimizable; and solving said constraints to find a layout which solvesfor the variables over the constraints. The system for automaticdocument layout on multi-function office equipment comprises means fordocument layout constraint acquisition; means for document layoutvariable specification which specifies a set of variables that can beadjusted to achieve a satisfactory layout; means forrelationship-constraint to optimization-constraint conversion whichexpresses said satisfactory layout as a set of constraints on said setof variables wherein at least one of said set of constraints isexpressed as being optimizable; and means for constraint optimizationfor solving said constraints to find a layout which solves for thevariables over said constraints.

Other objects, advantages, and salient features of the invention willbecome apparent from the detailed description which, taken inconjunction with the drawings, disclose the preferred embodiments of theinvention.

DESCRIPTION OF THE DRAWINGS

The preferred embodiment and other aspects of the invention will becomeapparent from the following detailed description when taken inconjunction with the accompanying drawings which are provided for thepurpose of describing the invention and not for the limitation thereof,in which:

FIG. 1 illustrates a document template which specifies that there aretwo areas that should be filled with content: areaA and areaB, and whichalso specifies that the positions and sizes of areaA and areaB can bechanged; and

FIG. 2 illustrates the resulting genome after following through theexample of FIG. 1.

DETAILED DESCRIPTION OF THE INVENTION

What is disclosed is a system and method for specifying a customdocument as a constraint optimization problem, and a method toautomatically create the specified document using one of a set of manyexisting constraint optimization algorithms. The document is modeled asa constraint optimization problem which combines both requiredconstraints with non-required design constraints that act asoptimization criteria. One of a set of many existing constraintoptimization algorithms is then used to solve the problem, resulting inan automatically generated document that is well designed because it hasoptimized some specified design criteria.

In particular, a document template is represented as a constraintoptimization problem, and therefore contains a set of variables, a valuedomain for each variable, a set of required constraints, and a set ofdesired constraints (i.e. optimization functions).

In this invention, the areas of the document to be filled with contentare modeled as problem variables, as are any parameters of the documentthat can be changed. As an example, consider the document template shownin FIG. 1. The template specifies that there are two areas that shouldbe filled with content: areaA and areaB. The template also specifiesthat the positions and sizes of areaA and areaB can be changed. Thus,the problem variables for this example are: areaA, areaB,areaA-topLeftX, areaA-topLeftY, areaB-topLeftX, areaB-topLeftY,areaA-width, areaA-height, areaB-width, areaB-height.

The constraint optimization formulation further specifies that eachproblem variable has a value domain consisting of the possible values toassign to that variable. This invention teaches that for variables thatare document areas to be filled with content (e.g., areaA and areaB ofFIG. 1), the value domains are the content pieces that are applicable toeach area. For variables that are document parameters, the value domainsare discretized ranges for those parameters, so that each potentialvalue for the parameter appears in the value domain e.g., 1 . . .MAXINT]. For variables whose value domains are content pieces, thedefault domain is set up to be all possible content pieces in theassociated content database, which is specified in the documenttemplate.

The required constraints specify relationships between variables and/orvalues that must hold in order for the resulting document to be valid.The desired constraints specify relationships between variables and/orvalues that we would like to satisfy, but aren't required in order forthe resulting document to be valid. Constraints may be unary (apply toone value/variable), binary (apply to two values/variables), or n-ary(apply to n values/variables), and in our invention are entered by theuser as part of the document template. An example of a required unaryconstraint in the document domain is: areaA must contain an image of acastle. An example of a required binary constraint is:areaA−topLeftY+areaA-height<areaB-topLeftY. If we had another variable(areaC), an example of a required 3-ary constraint is:areaA-width+areaB-width>areaC-width. In a variable data application ofthis invention (one of many possible applications), the constraintswould also refer to customer attributes (e.g., areaA must contain animage that is appropriate for customer1.age).

Desired constraints are represented as objective functions to maximizeor minimize. For example, a desired binary constraint might be theobjective function: f=areaA-width*areaA-height, to be maximized. If morethan one objective function is defined for the problem, the problembecomes a multi-criteria optimization problem. If it is a multi-criteriaoptimization problem, we sum the individual objective function scores toproduce the overall optimization score for a particular solution. We canfurthermore weight each of the desired constraints with a priority, sothat the overall optimization score then becomes a weighted sum of theindividual objective function scores.

Any one of the known existing constraint optminzation algorithms is thenapplied to create the final output document. This invention furtherdescribes a means to use a genetic algorithm (one of the many possibleconstraint optimization algorithms) for doing the constraintoptimization and thereby automatically creating a final output documentthat adheres not only to the required constraints, but also to a set ofdesired constraints.

In our genetic algorithm formulation of constraint optimization fordocument creation, the genome is built such that each gene in the genomeis a variable of the constraint problem. Following through our examplefrom FIG. 1, the resulting genome is shown in FIG. 2. The unaryconstraints are used to set up the allowable value domains for eachgene. These can be some default range, or input by the user.

In this invention, the fitness function is defined such that it returnsa fitness of 0 for any population members that do not meet the requiredconstraints, and for the members that do meet the required constraints,it returns a fitness score that is a sum of the scores of the individualdesired constraints. For instance, if we have the required constraints:C1: areaA-width<300C2: areaB-width<300And the desired constraints:C3: areaA-width=areaB-width, to be maximized (ranges from 0 to 1)C4: areaA-height=areaB-height, to be maximized (ranges from 0 to 1)Examples of fitness function for these desired constraints aref3=1−|areaA-width−areaB-width|/(areaA-width+areaB-width)f4=1−|areaA-height−areaB-height|/(areaA-width+areaB-height)

If we have a population member with areaA-width=350, areaA-height=350,areaB-width=400, areaB-height=200, the fitness function returns a scoreof 0. If, however, we have a population member with areaA-width=300,areaA-height=200, areaB-width=300, areaB-height=200, the fitnessfunction returns a score of 2. If we have a population member withareaA-width=225, areaA-height=200, areaB-width=300, areaB-height=200,the fitness function returns a score of 1.875.

Our formulation also extends to allow weighting of the various desiredconstraints. Thus, the document creator can specify that certain desiredconstraints are more important than others. For instance, we could haveconstraint C3 weighted with an importance of 1.5, and C4 weighted withan importance of 0.5, meaning that the two objects having the same widthis more important than the two objects having the same height. Thefitness function's overall score is then computed as a weighted sum ofthe individual desired constraints.

For instance, if we have a population member with areaA-width=225,areaA-height=200, areaB-width=300, areaB-height=200, desired constraintC3 returns 0.875, which is multiplied by C3's weight of 1.5, to get1.286. Desired constraint C4 returns 1, which is multiplied by C4'sweight of 0.5, to get 0.5. The overall fitness score is then1.125+0.5=1.786.

If, on the other hand, we have a population member with areaA-width=300,areaA-height=200, areaB-width=300, areaB-height=150, desired constraintC3 returns 1, which is multiplied by C3's weight of 1.5 to get 1.5.Desired constraint C4 returns 0.875, which is multiplied by C4's weightof 0.5, to get 0.438. The overall fitness score is then 1.5+0.438=1.938,thereby preferring the solution that violates C3 the least.

In the genetic algorithm implementation of this invention, we create aninitial population of chromosomes by selecting values for each gene, anddoing this for the desired number of population members. We evaluateeach member of this population according to the fitness function,resulting in a score for each population member. We then select the mostfit individuals (i.e., best fitness score) as parents for the newpopulation, and create a new population from the parents usingcrossover/mutation operations. We iterate through populations until wereach a specified stopping condition (e.g., a certain number ofiterations are complete, or until we have crossed a minimum thresholdfor the fitness function).

Thus, each genome is evaluated according to how well it satisfies orachieves the design qualities along with the other required constraints.This results in a generated document that not only satisfies therequired constraints, but that is also optimized for the specifieddesign qualities.

The system and method of the present invention has many advantages overthe prior art. Whereas the current constraint satisfaction approachesoften require many low-level layout constraints to be specified in orderto achieve a reasonable result, the genetic algorithm approach disclosedherein allows a specification of a few high-level desired constraintsand qualities—a much more intuitive and less user-demanding process.Another advantage of the constraint optimization approach describedherein is that it can find pleasing solutions for any combination ofcontent thereby enabling more dynamic custom document instances. Inaddition, selection of content can be influenced by the design criteriathat is included in the solving process by creating genes that specifythe number of items to include for each content area and, as the genevalue varies, the content items included vary as well. Another advantageof the present constraint-optimization system and method is that thevarious aesthetic criteria can be weighted and result in a differentoutput document based on the weightings (e.g., a different outputdocument would be generated if compactness was heavily weighted than ifpage utilization was heavily weighted).

While the invention is described with reference to a particularembodiment, this particular embodiment is intended to be illustrative,not limiting. Various modifications may be made without departing fromthe spirit and scope of the invention as defined in the amended claims.Modifications and alterations will occur to others upon reading andunderstanding this specification; therefore, it is intended that allsuch modifications and alterations are included insofar as they comewithin the scope of the appended claims or equivalents thereof.

What is desired to be secured by United States Letters Patent is:

1. A method for automatic document component layout comprising: (a)determining a set of variables that can be adjusted to achieve asatisfactory layout; (b) expressing the satisfactory layout as a set ofconstraints, the set of constraints including required constraints anddesired constraints, on the determined set of variables wherein at leastone of the desired constraints is expressed as being optimizable, eachrequired constraint specifying a relationship between a variable and adocument layout value, each desired constraint being an objectivefunction; (c) inputting a plurality of sets of document layout values,each set of document layout values representing a specific documentlayout; (d) solving the required constraints for each document layout;(e) solving the desired constraints for each document layout toestablish a score for each document layout; and (f) selecting thedocument layout having each solved required constraint relationship ofthe document layout satisfied and a highest score to be the satisfactorylayout.
 2. The method for automatic document component layout as inclaim 1, wherein each desired constraint is weighted.
 3. A method forautomatic document component layout comprising: (a) determining a set ofvariables that can be adjusted to achieve a satisfactory layout; (b)expressing the satisfactory layout as a set of constraints, the set ofconstraints including required constraints and desired constraints, onthe determined set of variables wherein at least one of the desiredconstraints is expressed as being optimizable, each required constraintspecifying a relationship between a variable and a document layoutvalue, each desired constraint being an objective function; (c)inputting a plurality of sets of document layout values, each set ofdocument layout values representing a specific document layout; (d)solving the required constraints for each document layout; (e) solvingthe desired constraints for each document layout to establish a scorefor each document layout; and (f) selecting the document layout havingeach solved required constraint relationship of the document layoutsatisfied and a lowest score to be the satisfactory layout.
 4. Themethod for automatic document component layout as in claim 3, whereineach desired constraint is weighted.
 5. A method for automatic documentcomponent layout comprising: (a) creating a population of documentlayout members, each document layout being represented by a plurality ofdocument layout values, each document layout value corresponding to adocument layout variable; (b) establishing a set of constraints, the setof constraints including required constraints and desired constraints,each required constraint specifying a relationship between a variableand a document layout value, each desired constraint being an objectivefunction; (c) solving the required constraints for each document layoutmember; (d) solving the desired constraints for each document layoutmember to establish a score for each document layout member; (e)selecting the document layout members having each solved requiredconstraint relationship of the document layout satisfied and a scoregreater that a predetermined score; (f) creating a new population ofchildren document layout members by performing crossover/mutationoperations upon the selected document layout members; (g) solving therequired constraints for each child document layout member; (h) solvingthe desired constraints for each child document layout member toestablish a score for each child document layout member; (i) selectingthe children document layout members having each solved requiredconstraint relationship of the document layout satisfied and a scoregreater that a predetermined score; and (j) re-iterating the creating,solving, and selecting processes until a termination condition isrealized.
 6. The method for automatic document component layout as inclaim 5, wherein the termination condition is defined as a failure toimprove the layout after a predetermined number of iterations.
 7. Themethod for automatic document component layout as in claim 5, whereinthe termination condition is defined as a predetermined number ofiterations.
 8. The method for automatic document component layout as inclaim 5, wherein the termination condition is defined as when theselecting process fails to select a document layout member from thepopulation that has each solved required constraint relationship of thedocument layout satisfied and a score greater that a predeterminedscore.